Tech Xplore

Image compression method combines classic techniques for greater efficiency and flexibility

In his research, Professor Marko Huhtanen from the University of Oulu, who specializes in applied and computational ...
Scientific Research Publishing

Dual-Dilated Large Kernel Convolution for Visual Attention Network ()

Cheung, K. , Siu, Y. and Chan, K. (2025) Dual-Dilated Large Kernel Convolution for Visual Attention Network. Intelligent ...
Mirage News

Efficient Multi-Wavelength Model for 3D Holograms

Computer-generated holography (CGH), as one of the most attractive next-generation three-dimensional (3D) display technology, possesses the capacity ...
IEEE

Self-Denoising of BOTDA Using Deep Convolutional Neural Networks

Abstract: We propose the self-denoising network (SDNet), a self-supervised network based on a convolutional neural network (CNN), for Brillouin trace denoising. With the target noisy image as the only ...
IEEE

Robust Deep Convolutional Dictionary Model With Alignment Assistance for Multi-Contrast MRI Super-Resolution

Abstract: Multi-contrast magnetic resonance imaging (MCMRI) super-resolution (SR) methods aims to leverage the complementary information present in multi-contrast images. However, existing methods ...
Frontiers

Deep learning super-resolution for temperature data downscaling: a comprehensive study using residual networks

Extreme weather events such as heatwaves, cyclones, floods, wildfires, and droughts are becoming more frequent due to climate change. Climate change causes shifts in biodiversity and impacts ...
Frontiers

Diagnosis of pneumonia from chest X-ray images using YOLO deep learning

Early and accurate diagnosis of pneumonia is crucial to improve cure rates and reduce mortality. Traditional chest X-ray analysis relies on physician experience, which can lead to subjectivity and ...
Scientific Research Publishing

Advanced Skin Disease Diagnosis and Treatment: Leveraging Convolutional Neural Networks for Image-Based Prediction and Comprehensive Health Assistance ()

Skin conditions are a worldwide health issue that requires prompt and accurate diagnosis in order to be effectively treated. This study presents a Convolutional Neural Network (CNN)-based automated ...